The issue of domain shift is one that has been addressed by many other works in literature. For instance, federated learning has been proposed to leverage many small datasets shared between hospitals to generate a single, large model from them [1]}. Another approach has been to modify network architectures to learn differently from the same data, and then use those various approaches cooperatively for performing the final prediction [2]}. Other studies, have made use of data augmentation, or have incorporated meta-learning strategies to exploit different characteristics from the training data in a self-supervised manner [3]}.
